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Studying temporal patterns of hydrology and water quality can assist in understanding hydrological processes, improving hydrological modeling, and water quality monitoring. Using wavelet analysis, we analyzed temporal patterns of three hydrological signals (precipitation, stream flow, and well water level) for three periods (15 years, 3 year, and a hydrological year). For three unevenly sampled water quality signals (nitrate, chloride, and sodium), the weighted wavelet Z-transform (WWZ) method was employed. The results showed that the wavelet analysis of hydrological signals showed advantages of detecting detailed temporal patterns compared to the classical Fourier analysis. No strong temporal pattern of precipitation was found for all three periods. For the 15 years’ continual monitoring datasets, strong consistent annual temporal pattern of well water level and an intermittent annual temporal pattern of stream …